This paper addresses multi-source composite disturbances in photovoltaic cleaning UAVs during continuous operation, including fluid-structure sloshing in the tank, time-varying mass decay, and near-wall unsteady aerodynamic interference. We propose an adaptive sliding-mode composite disturbance rejection strategy with physical-prior boundary constraints. Traditional controllers based on constant-rigid-body assumptions often induce trajectory overshoot or even instability under such conditions because they cannot effectively compensate the coupled effects of transient fluid impacts and mass loss. Therefore, we first establish a six-degree-of-freedom variable-mass nonlinear UAV dynamic model that includes additional Coriolis-related terms. On this basis, a collaborative disturbance-rejection architecture integrating intelligent sensing and online estimation modules is proposed: On one hand, a nonlinear disturbance observer (NDO) and a robust projection-based identification law are designed to achieve online decoupling and compensation of external low-frequency gusts and internal parameter drift; on the other hand, sloshing-force extrema extracted from fluid-structure simulations are used as dynamic constraint thresholds to construct a constrained adaptive sliding-mode controller (ASMC) with anti-chattering characteristics. Lyapunov theory proves the uniformly ultimately bounded (UUB) property of closed-loop states. Numerical simulations show that the proposed strategy confines roll-angle deviation within 0.15 rad under strong liquid-surface agitation and achieves zero-error altitude tracking with steady-state error below ±0.015 m during monotonic mass decay induced by continuous discharge. In addition, the physical-prior mechanism suppresses actuator chattering and saturation caused by high-frequency switching at the control source. The proposed architecture combines low computational cost with strong robustness, providing effective theoretical and technical support for engineering deployment of special liquid-carrying UAVs.
Weijia Li, Hexu Yang, Feng Xie et al.· International Conference on...· 0 citations
Digital State Capacity is the ability of governments to deploy ICT infrastructure and information systems to implement policy. This paper introduces a new measure of government ICT capacity based on an observable stock of deployable public-sector network infrastructure: public IPv4 address space held by government organisations. These address holdings are key inputs into digital administration because they support internet-facing systems, networked information exchange, and coordination across agencies and functions. The core panel covers approximately 150,000 country-entity records classified as government across more than 150 countries from 2019 to 2024 and can be disaggregated by administrative level and government function. In the 2019 to 2024 Admin-1 panel, government IP holdings are observed in 1,681 subnational regions across all years. We validate the measure at the crosscountry and subnational levels and apply it to government tasks related to corruption control and vaccination rollout. In illustrative country-year analysis, higher Digital State Capacity is associated with higher-quality governance and publicservice outcomes in the expected directions, including lower measured corruption and higher vaccination coverage. These associations are descriptive; they demonstrate the empirical relevance of the measure and are not causal estimates.
Patrick Healy, S. Angus, P. Raschky et al.· 0 citations
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